Integrating AI into TVET: Implications for semi-skilled occupations and jobs redesign

The rapid diffusion of artificial intelligence (AI) across economies and societies is reshaping the nature of work, skills demand, and pathways to inclusion. While policy debates and training initiatives on AI have so far focused predominantly on high-skilled and technical occupations, far less attention has been paid to how AI-enabled tools may affect semi-skilled and manual occupations, particularly those accessed through TVET. This gap risks reinforcing existing inequalities, especially in contexts where TVET serves as a key entry point to employment for vulnerable learners. 

Emerging evidence suggests that AI is reshaping work primarily through changes in tasks and workflows rather than through the disappearance of entire occupations. This shift places growing emphasis on how work is organised and performed, and on the distribution of cognitive and decision-making tasks within semi-skilled roles.

As AI-enabled applications become increasingly embedded in everyday life and work, the risk of a widening digital and AI divide is growing, not only in access to technology, but also in how work tasks are designed and who is able to engage in higher-value cognitive activities. Semi-skilled occupations such as hairdresser assistants, assistant cooks, cleaners, construction helpers, caregivers, shop assistants, and workshop aides are rarely targeted by digitalisation or AI strategies, despite their potential to benefit from simple, task-oriented applications. Used appropriately, AI tools can support these workers in practical ways—enhancing service quality, supporting basic planning and decision-making, and strengthening links between work, learning, and social participation.

Emerging practices suggest that AI can be meaningfully integrated into semi-skilled roles not by automating tasks, but by augmenting human work, embedding machine-generated insights into everyday workflows to support judgement, planning, communication and problem-solving. Examples include using AI applications to visualise hair styles and colours with clients, support meal planning and nutritional calculations in catering, or assist with task organisation and communication in service roles. However, such approaches remain largely absent from current TVET curricula and training strategies in many Partner Countries.

Against this backdrop, there is a growing need to explore how AI can be positioned as part of inclusive skills development and lifelong learning pathways — supporting employability, income progression and resilience by expanding the scope of cognitive and decision-making tasks within semi-skilled occupations, rather than displacing these roles altogether. This requires moving beyond a narrow focus on advanced digital skills and considering how AI can be embedded in semi-skilled training in ways that are accessible, relevant, and scalable.

Drawing on labour market evidence, policy analysis and international examples, this webinar explores how AI technologies and tools are affecting semi-skilled work through changes in tasks, roles and progression pathways, and what this means for TVET systems, programmes and providers preparing learners for these jobs.

You will soon find the agenda, presentations, webinar recording  and a short summary attached to this page.